1 citations · 1 across the 1 of their papers we have counts for
4 papers
Teacher-Student Domain Adaptation for Biosensor Models
Lawrence G. Phillips, David B. Grimes, Yihan Jessie Li
We present an approach to domain adaptation, addressing the case where data from the source domain is abundant, labelled data from the target domain is limited or non-existent, and…
Explanatory Masks for Neural Network Interpretability
Lawrence Phillips, Garrett Goh, Nathan Hodas
Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been…
Metric-Based Few-Shot Learning for Video Action Recognition
Chris Careaga, Brian Hutchinson, Nathan Hodas +1
In the few-shot scenario, a learner must effectively generalize to unseen classes given a small support set of labeled examples. While a relatively large amount of research has gon…
Sparse hierarchical representation learning on molecular graphs
Matthias Bal, Hagen Triendl, Mariana Assmann +6
Architectures for sparse hierarchical representation learning have recently been proposed for graph-structured data, but so far assume the absence of edge features in the graph. We…